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This article explores the concept of "lay summaries" in scientific research articles, which aim to make research findings more accessible to a wider audience. However, the article argues that these summaries often still contain complex language and are difficult for nonspecialists to understand. The article provides recommendations for authors, publishers, and editors on how to improve the accessibility of these summaries, focusing on reducing jargon and improving readability. The authors suggest using shorter sentences, simpler language, and active voice, and recommend that publishers and editors provide clearer instructions and examples. The goal is to increase the visibility and impact of research by making summaries more easily understood by a broader range of people. [Extracted from the article]

A variety of classification approaches are used to facilitate understanding, prediction, monitoring, and the management of lakes. However, broad‐scale applicability of current approaches is limited by either the need for in situ lake data, incompatibilities among approaches, or a lack of empirical testing of approaches based on ex situ data. We developed a new geographic classification approach for 476,697 lakes ≥ 1 ha in the conterminous U.S. based on lake archetypes representing end members along gradients of multiple geographic features. We identified seven lake archetypes with distinct combinations of climate, hydrologic, geologic, topographic, and morphometric properties. Individual lakes were assigned weights for each of the seven archetypes such that groups of lakes with similar combinations of archetype weights tended to cluster spatially (although not strictly contiguous) and to have similar limnological properties (e.g., concentrations of nutrients, chlorophyll a (Chl a), and dissolved organic carbon). Further, archetype lake classification improved commonly measured limnological relationships (e.g., between nutrients and Chl a) compared to a global model; a discrete archetype classification slightly outperformed an ecoregion classification; and considering lakes as continuous mixtures of archetypes in a more complex model further improved fit. Overall, archetype classification of US lakes as continuous mixtures of geographic features improved understanding and prediction of lake responses to limnological drivers and should help researchers and managers better characterize and forecast lake states and responses to environmental change. [ABSTRACT FROM AUTHOR]

The LAGOS‐US RESERVOIR data module classifies all 137,465 lakes ≥ 4 ha in the conterminous U.S. into three categories using a machine learning predictive model based on visual interpretation of lake outlines and a lake shape classification rule. Natural Lakes (NLs) are defined as naturally formed, lacking large, flow‐altering structures; Reservoir Class A's (RSVR_A) are defined as lakes likely human‐made or human‐altered by a large water control structure; and Reservoir Class B's (RSVR_Bs) are lakes likely human‐made but are not connected to streams and have a shape rare in NLs. We trained machine learning models on 12,162 manually classified lakes to predict assignment as an NL or RSVR, then further classified RSVRs based on NHD Fcodes, isolation, and angularity. Our classification indicates that > 46% of lakes ≥ 4 ha in the conterminous U.S. are reservoir lakes. These data can be easily combined with other LAGOS‐US modules and U.S. national databases for the broad‐scale study of reservoir lakes and NLs. [ABSTRACT FROM AUTHOR]

Depth is a fundamental property of lakes, essential for understanding and quantifying a range of biological, chemical, and physical processes of individual lakes as well as the collective functioning of the millions of lakes across the globe. Despite this importance, lake depth is rarely available for large numbers of lakes across the broad scales of regions and continents. We describe a new open‐access dataset, LAGOS‐US DEPTH, which contains 17,675 maximum depths and 6,137 mean depths for lakes in the conterminous United States. These data represent one of the largest compilations of lake depths in the world and are connected to other data products through the LAGOS‐US research platform. Here, we describe characteristics of lake maximum depth across the conterminous United States and identify gaps in data coverage that we encourage other researchers to fill by linking their own depth datasets for lakes within the LAGOS‐US spatial footprint. Extending this open‐access effort to include other regions and countries across the globe to build a more comprehensive and representative database of lake depth would better position scientists to quantify and articulate the critical roles that lakes play globally in biogeochemical cycling, maintaining biodiversity, and in maintaining the many ecosystem services that lakes provide. [ABSTRACT FROM AUTHOR]

Macroscale studies of aquatic ecosystems are needed to address many contemporary broad‐scale problems related to global change, particularly to inform national‐scale environmental policies. In this data paper, we fill two important gaps in data availability for lakes at the scale of the conterminous U.S., the lack of: (1) high‐resolution geographic representations of lakes and their watersheds and (2) an open data platform to connect disparate U.S. national‐scale lake datasets. We describe the LAGOS‐US LOCUS v1.0 data module that includes a detailed User Guide, which is part of the LAGOS‐US extensible research‐ready open data platform. This platform can be used to study the 479,950 lakes and reservoirs larger than or equal to 1 ha across the entire conterminous U.S. at multiple scales of space and time. The LOCUS module includes spatially‐explicit information on lakes and their watersheds, including location information, physical characteristics, and identifiers of other important national‐scale datasets. [ABSTRACT FROM AUTHOR]

Peer‐review and subject‐matter editing is the backbone of scientific publishing. However, early‐career researchers (ECRs) are given few opportunities to participate in the editorial process beyond reviewing articles. Thus, a disconnect exists: science needs high‐quality editorial talent to conduct, oversee and improve the publishing process, yet we dedicate few resources to building editorial talent nor giving ECRs formal opportunities to influence publishing from within. ECRs can contribute to the publishing landscape in unique ways given their insight into new and rapidly developing publishing trends (e.g. open science). Here, we describe a two‐way fellowship model that gives ECRs a "seat" at the editorial table of a field‐leading journal. We describe both the necessary framework and benefits that can stem from editorial fellowships for ECRs, editors, journals, societies, and the ​broader scientific community. [ABSTRACT FROM AUTHOR]

Although ecosystems respond to global change at regional to continental scales (i.e., macroscales), model predictions of ecosystem responses often rely on data from targeted monitoring of a small proportion of sampled ecosystems within a particular geographic area. In this study, we examined how the sampling strategy used to collect data for such models influences predictive performance. We subsampled a large and spatially extensive data set to investigate how macroscale sampling strategy affects prediction of ecosystem characteristics in 6,784 lakes across a 1.8‐million‐km2 area. We estimated model predictive performance for different subsets of the data set to mimic three common sampling strategies for collecting observations of ecosystem characteristics: random sampling design, stratified random sampling design, and targeted sampling. We found that sampling strategy influenced model predictive performance such that (1) stratified random sampling designs did not improve predictive performance compared to simple random sampling designs and (2) although one of the scenarios that mimicked targeted (non‐random) sampling had the poorest performing predictive models, the other targeted sampling scenarios resulted in models with similar predictive performance to that of the random sampling scenarios. Our results suggest that although potential biases in data sets from some forms of targeted sampling may limit predictive performance, compiling existing spatially extensive data sets can result in models with good predictive performance that may inform a wide range of science questions and policy goals related to global change. [ABSTRACT FROM AUTHOR]

Aquatic scientists require robust, accurate information about nutrient concentrations and indicators of algal biomass in unsampled lakes in order to understand and predict the effects of global climate and land‐use change. Historically, lake and landscape characteristics have been used as predictor variables in regression models to generate nutrient predictions, but often with significant uncertainty. An alternative approach to improve predictions is to leverage the observed relationship between water clarity and nutrients, which is possible because water clarity is more commonly measured than lake nutrients. We used a joint‐nutrient model that conditioned predictions of total phosphorus, nitrogen, and chlorophyll a on observed water clarity. Our results demonstrated substantial reductions (8–27%; median = 23%) in prediction error when conditioning on water clarity. These models will provide new opportunities for predicting nutrient concentrations of unsampled lakes across broad spatial scales with reduced uncertainty. [ABSTRACT FROM AUTHOR]

Ecological research increasingly relies on broad‐scale databases containing information collected by personnel from a variety of sources, including government agencies, universities, and citizen‐science programs. However, the contribution of citizen‐science programs to these databases is not well known. We analyzed one such database to quantify the contribution of citizen science to lake water‐quality data from seven US states. Citizen‐science programs not only provided over half of the observations for commonly sampled water‐quality measures (water clarity, nutrients, and algal biomass) from the past 31 years, but also contributed to the majority of long‐term monitoring (>15 years) for selected measures in lakes. While previous studies have demonstrated the usefulness of citizen science for research, management, policy, and public engagement, our study demonstrates that citizen science can also make valuable contributions to populating broad‐scale ecological databases. Strengthening partnerships between citizen‐science programs and monitoring agencies can help maintain and expand spatial and temporal data coverage during the "big data" era of ecology. [ABSTRACT FROM AUTHOR]

Editors are often described as gatekeepers of scientific publishing, as they are responsible for maintaining journal standards, deciding what is published, and ultimately guiding discourse. Scientists who are journal editors gain career benefits, yet these are rarely described to early career researchers, much less how to prepare for such a role. Additionally, disparities at the editorial level could impact which scientists receive benefits of filling these roles. To better characterize the demographics and professional experiences of current associate editors, while also highlighting the benefits and potential challenges to this position, we conducted a survey of associate editors for the Association for the Sciences of Limnology & Oceanography society journals. Our results highlight potential demographic disparities present in the editorial pool, including that non‐native English speaking editors assume the role after obtaining more experience serving as a peer reviewer than native English speaking editors. Our results also highlight several rewards along with challenging components of being an editor. We hope our results can inform early career researchers on steps they can take to prepare themselves for editorial work, as well as provide strategies for scientific societies to minimize editorial board disparities. [ABSTRACT FROM AUTHOR]

Given how important lakes are to people, it might seem safe to assume that careful thought has been put into the naming of lakes, and that lake names reflect the high societal value people place on lakes. We examined these assumptions by analyzing the official names in the U.S. Geographic Names Information System for the 479,950 lakes ≥ 1 ha in the conterminous U.S. We found that 83% of lakes were unnamed and most of these were small lakes with 80% of unnamed lakes being smaller than 4 ha. Based on the 83,115 named lakes, we found that lake names reflect peoples' everyday lives, that lakes can inspire creativity (although the most common lake name is "Mud"), that Native American and indigenous languages have played a role in lake naming, and that there are regional differences in lake names. Unfortunately, we also found that derogatory terms were part of some lake names. We advocate for thoughtful and inclusive official naming of the 400,000 unnamed lakes in the U.S., as well as renaming of the lakes with derogatory terms to help focus attention on the importance of lakes to local communities and nations. [ABSTRACT FROM AUTHOR]

The Convention on Biological Diversity (https://www.cbd.int/) recommends globally protecting ≥ 17% of ecologically representative freshwaters by 2020 to sustain critical ecosystem services and rapidly declining freshwater biodiversity. We examined whether current conservation efforts meet this target for lakes (≥ 1 ha) across the continental U.S. and Environmental Protection Agency ecoregions using the U.S. Protected Areas Database. How one defines lake protection matters: 17.8% of lakes fell within multiuse or strictly protected areas, but only 7.5% of lakes had ≥ 80% of their catchments in strictly protected areas. Protected lakes occurred disproportionately in the lake‐poor western U.S. and most lake‐rich regions fell short of the 17% target. Lakes connected to streams and other lakes were disproportionately protected relative to headwater and isolated lakes, which are important for ecosystem services and biodiversity. Meeting conservation targets requires protecting thousands of additional U.S. lakes and catchments across more diverse ecological settings and explicitly considering connectivity. [ABSTRACT FROM AUTHOR]

Although spatial and temporal variation in ecological properties has been well‐studied, crucial knowledge gaps remain for studies conducted at macroscales and for ecosystem properties related to material and energy. We test four propositions of spatial and temporal variation in ecosystem properties within a macroscale (1000 km's) extent. We fit Bayesian hierarchical models to thousands of observations from over two decades to quantify four components of variation – spatial (local and regional) and temporal (local and coherent); and to model their drivers. We found strong support for three propositions: (1) spatial variation at local and regional scales are large and roughly equal, (2) annual temporal variation is mostly local rather than coherent, and, (3) spatial variation exceeds temporal variation. Our findings imply that predicting ecosystem responses to environmental changes at macroscales requires consideration of the dominant spatial signals at both local and regional scales that may overwhelm temporal signals. [ABSTRACT FROM AUTHOR]

Wildfires are becoming larger and more frequent across much of the United States due to anthropogenic climate change. No studies, however, have assessed fire prevalence in lake watersheds at broad spatial and temporal scales, and thus it is unknown whether wildfires threaten lakes and reservoirs (hereafter, lakes) of the United States. We show that fire activity has increased in lake watersheds across the continental United States from 1984 to 2015, particularly since 2005. Lakes have experienced the greatest fire activity in the western United States, Southern Great Plains, and Florida. Despite over 30 years of increasing fire exposure, fire effects on fresh waters have not been well studied; previous research has generally focused on streams, and most of the limited lake‐fire research has been conducted in boreal landscapes. We therefore propose a conceptual model of how fire may influence the physical, chemical, and biological properties of lake ecosystems by synthesizing the best available science from terrestrial, aquatic, fire, and landscape ecology. This model also highlights emerging research priorities and provides a starting point to help land and lake managers anticipate potential effects of fire on ecosystem services provided by fresh waters and their watersheds. [ABSTRACT FROM AUTHOR]

Lake water residence time and depth are known to be strong predictors of phosphorus (P) retention. However, there is substantial variation in P retention among lakes with the same depth and residence time. One potential explanatory factor for this variation is differences in freshwater connectivity of lakes (i.e., the type and amount of freshwater connections to a lake), which can influence watershed P trapping or the particulate load fraction of P delivered to lakes via stream connections. To examine the relationship between P retention and connectivity, we quantified several different measures of connectivity including those that reflect downstream transport of material (sediment, water, and nutrients) within lake‐stream networks (lake‐stream‐based metrics) as well as those that reflect transport of material from hillslope and riparian areas adjacent to watershed stream networks (stream‐based metrics). Because it is not always clear what spatial extent is appropriate for determining functional differences in connectivity among lakes, we compared connectivity metrics at two important spatial extents: the lake subwatershed extent and the lake watershed extent. We found that variation in P retention among lakes was more strongly associated with connectivity metrics measured at the broader lake watershed extent rather than metrics measured at the finer lake subwatershed extent. Our results suggest that both connectivity between lakes and streams as well as connectivity of lakes and their terrestrial watersheds influence P retention. [ABSTRACT FROM AUTHOR]

Growth of macroscale limnological research has been accompanied by an increase in secondary datasets compiled from multiple sources. We examined patterns of data availability in LAGOS‐NE, a dataset derived from 87 sources, to identify biases in availability of lake water quality data and to consider how such biases might affect perceived patterns at a subcontinental scale. Of eight common water quality parameters, variables indicative of trophic state (Secchi, chlorophyll, and total P) were most abundant in terms of total observations, lakes sampled, and long‐term records, whereas carbon variables (true color and dissolved organic carbon) were scarcest. Most data were collected during summer from larger (≥ 20 ha) lakes over 1–3 yr. Approximately 80% of data for each variable is derived from ~ 20% of sampled lakes. Long‐term (≥ 20 yr) records were rare and spatially clustered. Data availability is linked to major management challenges (eutrophication and acid rain), citizen science, and a few programs that quantify C and N variables. Resampling exercises suggested that correcting for the surface area sampling bias did not substantially change statistical distributions of the eight variables. Further, estimating a lake's long‐term median Secchi, chlorophyll, and total P using average record lengths had high uncertainty, but modest increases in sample size to > 5 yr yielded estimates with manageable error. Although the specific nature of sampling biases may vary among regions, we expect that they are widespread. Thus, large integrated datasets can and should be used to identify tendencies in how lakes are studied and to address these biases as part broad‐scale limnological investigations. [ABSTRACT FROM AUTHOR]

In this article, I provide six simple steps for authors to make their data available and meet the most common data publishing requirements for both open‐access and non‐open–access journals. These steps are simple and can easily be integrated into authors' workflows when conducting research and writing research articles. The steps include: deciding authorship of the dataset vs. authorship of the research article; exporting the data needed for all article analyses into archivable (preferably plain text) files using simple table formats; writing the metadata; depositing the data and metadata in a data repository; writing a data availability statement in the article; and citing the dataset in the methods and literature cited sections. Authors who implement these guidelines will reap many benefits for their science while also following best practices for open, robust, and reproducible science. [ABSTRACT FROM AUTHOR]

Aim: We aimed to measure the dominant spatial patterns in ecosystem properties (such as nutrients and measures of primary production) and the multi‐scaled geographical driver variables of these properties and to quantify how the spatial structure of pattern in all of these variables influences the strength of relationships among them. Location and time period: We studied > 8,500 lakes in a 1.8 million km2 area of Northeast U.S.A. Data comprised 10‐year medians (2002–2011) for measured ecosystem properties, long‐term climate averages and recent land use/land cover variables. Major taxa studied: We focused on ecosystem properties at the base of aquatic food webs, including concentrations of nutrients and algal pigments that are proxies of primary productivity. Methods: We quantified spatial structure in ecosystem properties and their geographical driver variables using distance‐based Moran eigenvector maps (dbMEMs). We then compared the similarity in spatial structure for all pairs of variables with the correlation between variables to illustrate how spatial structure constrains relationships among ecosystem properties. Results: The strength of spatial structure decreased in order for climate, land cover/use, lake ecosystem properties and lake and landscape morphometry. Having a comparable spatial structure is a necessary condition to observe a strong relationship between a pair of variables, but not a sufficient one; variables with very different spatial structure are never strongly correlated. Lake ecosystem properties tended to have an intermediary spatial structure compared with that of their main drivers, probably because climate and landscape variables with known ecological links induce spatial patterns. Main conclusion: Our empirical results describe inherent spatial constraints that dictate the expected relationships between ecosystem properties and their geographical drivers at macroscales. Our results also suggest that understanding the spatial scales at which ecological processes operate is necessary to predict the effects of multi‐scaled environmental changes on ecosystem properties. [ABSTRACT FROM AUTHOR]

Recent debate over the scope of the U.S. Clean Water Act underscores the need to develop a robust body of scientific work that defines the connectivity between freshwater systems and people. Coupled natural and human systems (CNHS) modeling is one tool that can be used to study the complex, reciprocal linkages between human actions and ecosystem processes. Well-developed CNHS models exist at a conceptual level, but the mapping of these system representations in practice is limited in capturing these feedbacks. This article presents a paired conceptual--empirical methodology for functionally capturing feedbacks between human and natural systems in freshwater lake catchments, from human actions to the ecosystem and from the ecosystem back to human actions. We address extant challenges in CNHS modeling, which arise from differences in disciplinary approach, model structure, and spatiotemporal resolution, to connect a suite of models. In doing so, we create an integrated, multi-disciplinary tool that captures diverse processes that operate at multiple scales, including land-management decision-making, hydrologic-solute transport, aquatic nutrient cycling, and civic engagement. In this article, we build on this novel framework to advance cross-disciplinary dialogue to move CNHS lake-catchment modeling in a systematic direction and, ultimately, provide a foundation for smart decision-making and policy. [ABSTRACT FROM AUTHOR]

Abstract: Publication is the key means by which science is disseminated, with evaluation by journal editors and peer reviewers an important component of the scientific process. Peer reviews are, however, a typically occluded genre of documents not publicly available. Consequently, relatively little is known about peer reviews, including what makes them relevant to editors who are assessing submitted manuscripts. Here we aim to address this knowledge gap by answering the questions: (1) Does reviewer and editor (dis)agreement on the manuscript decision (i.e., accept, minor revision, major revision, reject) relate to how editors assess overall review quality? and, (2) What are the characteristics of review text that distinguish high quality reviews from lower quality reviews for editors? We analyzed 49 reviews of 26 manuscript submissions to Limnology and Oceanography: Letters. We found editor perception of review quality was based on review content rather than if there was agreement on the manuscript decision. Specifically, reviews judged by editors to be ‘highly relevant’ rather than ‘sufficient’ were typically: longer; included more comments related to study goals, analyses conducted, and resulting claims; and contained more descriptive terms related to the manuscript's importance. Reviewers who consider these factors may produce reviews most relevant to editor decisions. [ABSTRACT FROM AUTHOR]

The United States (U.S.) has faced major environmental changes in recent decades, including agricultural intensification and urban expansion, as well as changes in atmospheric deposition and climate-all of which may influence eutrophication of freshwaters. However, it is unclear whether or how water quality in lakes across diverse ecological settings has responded to environmental change. We quantified water quality trends in 2913 lakes using nutrient and chlorophyll (Chl) observations from the Lake Multi-Scaled Geospatial and Temporal Database of the Northeast U.S. ( LAGOS- NE), a collection of preexisting lake data mostly from state agencies. LAGOS- NE was used to quantify whether lake water quality has changed from 1990 to 2013, and whether lake-specific or regional geophysical factors were related to the observed changes. We modeled change through time using hierarchical linear models for total nitrogen ( TN), total phosphorus ( TP), stoichiometry ( TN: TP), and Chl. Both the slopes (percent change per year) and intercepts (value in 1990) were allowed to vary by lake and region. Across all lakes, TN declined at a rate of 1.1% year−1, while TP, TN: TP, and Chl did not change. A minority (7%-16%) of individual lakes had changing nutrients, stoichiometry, or Chl. Of those lakes that changed, we found differences in the geospatial variables that were most related to the observed change in the response variables. For example, TN and TN: TP trends were related to region-level drivers associated with atmospheric deposition of N; TP trends were related to both lake and region-level drivers associated with climate and land use; and Chl trends were found in regions with high air temperature at the beginning of the study period. We conclude that despite large environmental change and management efforts over recent decades, water quality of lakes in the Midwest and Northeast U.S. has not overwhelmingly degraded or improved. [ABSTRACT FROM AUTHOR]

Inland water bodies and their surface hydrologic connections are active components in the landscape, influencing multiple ecological processes that can propagate to broad-scale phenomena such as regional nutrient and carbon cycles and metapopulation dynamics. However, while lake, wetland, and stream abundance has been estimated at regional and global extents, less attention has been paid to freshwater connectivity attributes among aquatic systems at macroscales. Thus, regional to continental patterns of freshwater abundance and connectivity are poorly understood. We measured lake, wetland, and stream abundance and surface connectivity attributes (i.e., landscape position within stream networks) at a subcontinental extent in the Midwest and Northeast United States to characterize macroscale spatial patterns of the freshwater landscape (i.e., abundance and connectivity attributes of lakes, wetlands, and streams). We found that lake and wetland abundance exhibited opposite spatial patterns from stream density that generally followed glaciation extent boundaries--lake and wetland abundance was high north of the glaciation boundary, whereas stream density was high south of the glaciation boundary. Freshwater connectivity attributes exhibited distinct spatial patterns as defined by our integrated freshwater clusters and revealed a layer of complexity not captured by abundance measures. Patterns of freshwater abundance and connectivity in the study extent were associated primarily with glaciation and secondarily with hydrogeomorphic (e.g., surficial geology and topography), climate (e.g., runoff), and land-use (e.g., agriculture) variables, providing insight into potential drivers of freshwater composition and distribution. The connectivity spatial patterns observed suggest that relying solely on freshwater abundance measures in macroscale analyses omits unique information on the structural attributes of freshwater systems that can be critical to key ecological processes. Adopting an integrated freshwater landscape framework to study and manage freshwaters is essential as freshwater systems face broad-scale disturbances that may alter hydrologic connections and subsequently may impact ecosystem processes and services. [ABSTRACT FROM AUTHOR]

Production in many ecosystems is co-limited by multiple elements. While a known suite of drivers associated with nutrient sources, nutrient transport, and internal processing controls concentrations of phosphorus (P) and nitrogen (N) in lakes, much less is known about whether the drivers of single nutrient concentrations can also explain spatial or temporal variation in lake N:P stoichiometry. Predicting stoichiometry might be more complex than predicting concentrations of individual elements because some drivers have similar relationships with N and P, leading to a weak relationship with their ratio. Further, the dominant controls on elemental concentrations likely vary across regions, resulting in context dependent relationships between drivers, lake nutrients and their ratios. Here, we examine whether known drivers of N and P concentrations can explain variation in N:P stoichiometry, and whether explaining variation in stoichiometry differs across regions. We examined drivers of N:P in ~2,700 lakes at a sub-continental scale and two large regions nested within the sub-continental study area that have contrasting ecological context, including differences in the dominant type of land cover (agriculture vs. forest). At the sub-continental scale, lake nutrient concentrations were correlated with nutrient loading and lake internal processing, but stoichiometry was only weakly correlated to drivers of lake nutrients. At the regional scale, drivers that explained variation in nutrients and stoichiometry differed between regions. In the Midwestern U.S. region, dominated by agricultural land use, lake depth and the percentage of row crop agriculture were strong predictors of stoichiometry because only phosphorus was related to lake depth and only nitrogen was related to the percentage of row crop agriculture. In contrast, all drivers were related to N and P in similar ways in the Northeastern U.S. region, leading to weak relationships between drivers and stoichiometry. Our results suggest ecological context mediates controls on lake nutrients and stoichiometry. Predicting stoichiometry was generally more difficult than predicting nutrient concentrations, but human activity may decouple N and P, leading to better prediction of N:P stoichiometry in regions with high anthropogenic activity. [ABSTRACT FROM AUTHOR]

Understanding broad-scale ecological patterns and processes often involves accounting for regional-scale heterogeneity. A common way to do so is to include ecological regions in sampling schemes and empirical models. However, most existing ecological regions were developed for specific purposes, using a limited set of geospatial features and irreproducible methods. Our study purpose was to: (1) describe a method that takes advantage of recent computational advances and increased availability of regional and global data sets to create customizable and reproducible ecological regions, (2) make this algorithm available for use and modification by others studying different ecosystems, variables of interest, study extents, and macroscale ecology research questions, and (3) demonstrate the power of this approach for the research question-How well do these regions capture regional-scale variation in lake water quality? To achieve our purpose we: (1) used a spatially constrained spectral clustering algorithm that balances geospatial homogeneity and region contiguity to create ecological regions using multiple terrestrial, climatic, and freshwater geospatial data for 17 northeastern U.S. states (~1,800,000 km2); (2) identified which of the 52 geospatial features were most influential in creating the resulting 100 regions; and (3) tested the ability of these ecological regions to capture regional variation in water nutrients and clarity for ~6,000 lakes. We found that: (1) a combination of terrestrial, climatic, and freshwater geospatial features influenced region creation, suggesting that the oft-ignored freshwater landscape provides novel information on landscape variability not captured by traditionally used climate and terrestrial metrics; and (2) the delineated regions captured macroscale heterogeneity in ecosystem properties not included in region delineation-approximately 40% of the variation in total phosphorus and water clarity among lakes was at the regional scale. Our results demonstrate the usefulness of this method for creating customizable and reproducible regions for research and management applications. [ABSTRACT FROM AUTHOR]

Macroscale studies of ecological phenomena are increasingly common because stressors such as climate and land-use change operate at large spatial and temporal scales. Cross-scale interactions (CSIs), where ecological processes operating at one spatial or temporal scale interact with processes operating at another scale, have been documented in a variety of ecosystems and contribute to complex system dynamics. However, studies investigating CSIs are often dependent on compiling multiple data sets from different sources to create multithematic, multiscaled data sets, which results in structurally complex, and sometimes incomplete data sets. The statistical power to detect CSIs needs to be evaluated because of their importance and the challenge of quantifying CSIs using data sets with complex structures and missing observations. We studied this problem using a spatially hierarchical model that measures CSIs between regional agriculture and its effects on the relationship between lake nutrients and lake productivity. We used an existing large multithematic, multiscaled database, LAke multiscaled GeOSpatial, and temporal database (LAGOS), to parameterize the power analysis simulations. We found that the power to detect CSIs was more strongly related to the number of regions in the study rather than the number of lakes nested within each region. CSI power analyses will not only help ecologists design large-scale studies aimed at detecting CSIs, but will also focus attention on CSI effect sizes and the degree to which they are ecologically relevant and detectable with large data sets. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the editor gives the information about being selected as the founding editor in chief for American Society of Limnology and Oceanography ASLO's new journal, Limnology and Oceanography Letters.

Ecologists are increasingly discovering that ecological processes are made up of components that are multi-scaled in space and time. Some of the most complex of these processes are cross-scale interactions (CSIs), which occur when components interact across scales. When undetected, such interactions may cause errors in extrap-olation from one region to another. CSIs, particularly those that include a regional scaled component, have not been systematically investigated or even reported because of the challenges of acquiring data at sufficiently broad spatial extents. We present an approach for quantifying CSIs and apply it to a case study investigating one such interaction, between local and regional scaled land-use drivers of lake phosphorus. Ultimately, our approach for investigating CSIs can serve as a basis for efforts to understand a wide variety of multi-scaled prob-lems such as climate change, land-use/land-cover change, and invasive species. [ABSTRACT FROM AUTHOR]

Interdisciplinary collaboration is essential to understand ecological systems at scales critical to human decision making. Current reward structures are problematic for scientists engaged in interdisciplinary research, particu-larly early career researchers, because academic culture tends to value only some research outputs, such as pri-mary-authored publications. Here, we present a framework for the costs and benefits of collaboration, with a focus on early career stages, and show how the implementation of novel measures of success can help defray the costs of collaboration. Success measures at team and individual levels include research outputs other than publications, including educational outcomes, dataset creation, outreach products (eg blogs or social media), and the application of scientific results to policy or management activities. Promotion and adoption of new measures of success will require concerted effort by both collaborators and their institutions. Expanded mea-sures should better reflect and reward the important work of both disciplinary and interdisciplinary teams at all career stages, and help sustain and stimulate a collaborative culture within ecology. [ABSTRACT FROM AUTHOR]

Collaborative research teams are a necessary and desirable component of most scientific endeavors. Effective col-laborative teams exhibit important research outcomes, far beyond what could be accomplished by individuals working independently. These teams are made up of researchers who are committed to a common purpose, approach, and performance goals for which they hold themselves mutually accountable. We call such collabora-tions "high-performing collaborative research teams". Here, we share lessons learned from our collective experi-ence working with a wide range of collaborative teams and structure those lessons within a framework developed from literature in business, education, and a relatively new discipline, "science of team science". We propose that high-performing collaborative research teams are created and maintained when team diversity (broadly defined) is effectively fostered and interpersonal skills are taught and practiced. Finally, we provide some strategies to fos-ter team functioning and make recommendations for improving the collaborative culture in ecology. [ABSTRACT FROM AUTHOR]

An important goal of macrosystems ecology (MSE) research is to advance understanding of ecological systems at both fine and broad temporal and spatial scales. Our premise in this paper is that MSE projects require inte-grated information management at their inception. Such efforts will lead to improved communication and sharing of knowledge among diverse project participants, better science outcomes, and more transparent and accessible (ie "open") science. We encourage researchers to "complete the data life cycle" by publishing well-documented datasets, thereby facilitating re-use of the data to answer new and different questions from the ones conceived by those involved in the original projects. The practice of documenting and submitting datasets to data repositories that are publicly accessible ensures that research results and data are available to and use-able by other researchers, thus fostering open science. However, ecologists are often unfamiliar with the require-ments and information management tools for effectively preserving data and receive little institutional or pro-fessional incentive to do so. Here, we provide recommendations for achieving these ends and give examples from current MSE projects to demonstrate why information management is critical for ensuring that scientific results can be reproduced and that data can be shard for future use. [ABSTRACT FROM AUTHOR]

Macrosystems ecology is the study of diverse ecological phenomena at the scale of regions to continents and their interactions with phenomena at other scales. This emerging subdiscipline addresses ecological questions and environmental problems at these broad scales. Here, we describe this new field, show how it relates to modern ecological study, and highlight opportunities that stem from taking a macrosystems perspective. We present a hierarchical framework for investigating macrosystems at any level of ecological organization and in relation to broader and finer scales. Building on well-established theory and concepts from other subdisci-plines of ecology, we identify feedbacks, linkages among distant regions, and interactions that cross scales of space and time as the most likely sources of unexpected and novel behaviors in macrosystems. We present three examples that highlight the importance of this multiscaled systems perspective for understanding the ecology of regions to continents. [ABSTRACT FROM AUTHOR]

Summary 1. For north temperate lakes, the well-studied empirical relationship between phosphorus (as measured by total phosphorus, TP), the most commonly limiting nutrient and algal biomass (as measured by chlorophyll a, CHL) has been found to vary across a wide range of landscape settings. Variation in the parameters of these TP-CHL regressions has been attributed to such lake variables as nitrogen/phosphorus ratios, organic carbon and alkalinity, all of which are strongly related to catchment characteristics (e.g. natural land cover and human land use). Although this suggests that landscape setting can help to explain much of the variation in ecoregional TP-CHL regression parameters, few studies have attempted to quantify relationships at an ecoregional spatial scale. 2. We tested the hypothesis that lake algal biomass and its predicted response to changes in phosphorus are related to both local-scale features (e.g. lake and catchment) and ecoregional-scale features, all of which affect the availability and transport of covarying solutes such as nitrogen, organic carbon and alkalinity. Specifically, we expected that land use and cover, acting at both local and ecoregional scales, would partially explain the spatial pattern in parameters of the TP-CHL regression. 3. We used a multilevel modelling framework and data from 2105 inland lakes spanning 35 ecoregions in six US states to test our hypothesis and identify specific local and ecoregional features that explain spatial heterogeneity in TP-CHL relationships. We include variables such as lake depth, natural land cover (for instance, wetland cover in the catchment of lakes and in the ecoregions) and human land use (for instance, agricultural land use in the catchment of lakes and in the ecoregions). 4. There was substantial heterogeneity in TP-CHL relationships across the 35 ecoregions. At the local scale, CHL was negatively and positively related to lake mean depth and percentage of wooded wetlands in the catchment, respectively. At the ecoregional scale, the slope parameter was positively related to the percentage of pasture in an ecoregion, indicating that CHL tends to respond more rapidly to changes in TP where there are high levels of agricultural pasture than where there is little. The intercept (i.e. the ecoregion-average CHL) was negatively related to the percentage of wooded wetlands in the ecoregion. 5. By explicitly accounting for the hierarchical nature of lake-landscape interactions, we quantified the effects of landscape characteristics on the response of CHL to TP at two spatial scales. We provide new insight into ecoregional drivers of the rate at which algal biomass responds to changes in nutrient concentrations. Our results also indicate that the direction and magnitude of the effects of certain land use and cover characteristics on lake nutrient dynamics may be scale dependent and thus likely to represent different underlying mechanisms regulating lake productivity. [ABSTRACT FROM AUTHOR]

Science is moving quickly toward open access of peer-reviewed scientific articles I and i the data they report. ASLO has recognized this important trend and embraced Open Access publication by making open-access options available to authors in two of its journals ( I Limnology and Oceanography i and I Limnology and Oceanography Methods i ), while also launching a fully open-access journal, I Limnology and Oceanography Letters i , in 2016. [Extracted from the article]

An introduction to the journal is presented in which the editor demonstrate the need to integrate the single-investigator model of science in ecology with a collaborative and interdisciplinary approach.

We quantified relationships between local wetland cover in the riparian lake buffer and lake total phosphorus (TP) and water color (color) using multilevel mixed-effects models that also incorporate landscape features such as hydrogeomorphology and land use at broad regional scales to determine the following: (1) Within regions, are local wetland relationships with TP and color affected by interactions with local land use or hydrogeomorphic variables? (2) Across regions, are local wetland relationships with TP and color different? And if so, (3) Are differences in local wetland relationships with TP and color a result of cross-scale interactions? We answered these questions by analyzing TP, color, and multiscaled landscape data for 1790 north temperate lakes. Local wetland-TP and wetland-color relationships were not affected by local-scale interactions. However, these same relationships were different when compared across regions, and these differences were related to cross-scale interactions with regional landscape characteristics. For example, regional human land use affected local wetland-TP relationships such that in regions with high amounts of agriculture, local wetlands were associated with decreased lake TP. However, in regions with low amounts of agriculture, local wetlands were associated with increased lake TP. In contrast, regional hydrogeomorphic characteristics influenced local wetland-color relationships such that in regions with high groundwater contribution, the strength of local wetland relationships were weak. Regional landscape setting influences local wetland relationships with TP and color through cross-scale interactions, and lake TP and color are controlled by both local-scale wetland extent and regional-scale landscape variables. [ABSTRACT FROM AUTHOR]

We examined spatial patterns of trends in ice phenology and duration for 65 waterbodies across the Great Lakes region (Minnesota, Wisconsin, Michigan, Ontario, and New York) during a recent period of rapid climate warming (1975-2004). Average rates of change in freeze (3.3 d decade-1) and breakup (22.1 d decade-1) dates were 5.8 and 3.3 times more rapid, respectively, than historical rates (1846-1995) for Northern Hemisphere waterbodies. Average ice duration decreased by 5.3 d decade-1. Over the same time period, average fall through spring temperatures in this region increased by 0.7°C decade-1, while the average number of days with snow decreased by 5.0 d decade21, and the average snow depth on those days decreased by 1.7 cm decade-1. Breakup date and ice duration trends varied over the study area, with faster changes occurring in the southwest. Trends for each site were compared to static waterbody characteristics and meteorological variables and their trends. The trend toward later freeze date was stronger in large, low-elevation waterbodies; however, freeze date trends had no geographic patterns or relationships to meteorological variables. Variability in the strength of trends toward earlier breakup was partially explained by spatial differences in the rate of change in the number of days with snow cover, mean snow depth, air temperature (warmer locations showed stronger trends), and rate of change in air temperature. Differences in ice duration trends were explained best by a combination of elevation and the local rate of change in either temperature or the number of days with snow cover. [ABSTRACT FROM AUTHOR]

To improve our understanding of lake landscape position, we compared four metrics based on different aspects of lake surface hydrologic connections: (1) "lake hydrology," which is a general measure of lake surface hydrologic position, (2) "lake order," which measures connections to streams by stream order, (3) "lake network number," which measures connections to other lakes, and (4) "lake network complexity," which measures the complexity of connections to other lakes (in a chain or branched). We sampled 71 lakes in northern Michigan, U.S.A. and measured lake landscape position and landscape characteristics around each lake (e.g., land use/cover and geology) to answer two questions: (1) which metric of landscape position explains the most variation in lake water chemistry/clarity? and (2) what landscape and physical features are also related to landscape position? All four landscape position metrics explained significant variation in some water chemistry/clarity variables. However, lake order, the metric based on stream order, consistently explained the most variation, ranging from 22% (dissolved organic carbon) to 53% (conductivity and calcium), with lake hydrology, the metric based on both streams and lakes, explaining similar amounts of variation to lake order, but less overall. Landscape position was also significantly related to both lake morphometry and the proportion of wetland types in buffer areas, which may help explain why landscape position is related to lake water chemistry and clarity variables. [ABSTRACT FROM AUTHOR]

1. Within a lake district of relatively homogeneous geomorphology, the responses of lakes to climate are influenced by the complexity of the hydrogeologic setting, position in the landscape, and lake-specific biological and physical features. We examined lake chemical responses to drought in surface water- and groundwater-dominated districts to address two general questions. (1) Are spatial patterns in chemical dynamics among lakes uniform and synchronous within a lake district, suggesting broad geomorphic controls; variable in a spatially explicit pattern, with synchrony related to landscape position, suggesting hydrologic flowpath controls; or spatially unstructured and asynchronous, suggesting overriding control by lake-specific factors? (2) Are lake responses to drought a simple function of precipitation quantity or are they dictated by more complex interactions among climate, unique lake features, and hydrologic setting? 2. Annual open-water means for epilimnetic concentrations of chloride, calcium, sulfate, ANC, DOC, total nitrogen, silica, total phosphorus, and chlorophyll a measured between 1982 and 1995 were assembled for lakes in the Red Lake and ELA districts of north-western Ontario, the Muskoka – Dorset district in south-central Ontario, and the Northern Highland district of Wisconsin. Within each district, we compared responses of lakes classified by landscape position into highland or lowland, depending on relative location within the local to regional hydrologic flow system. Synchrony, defined as a measure of the similarity in inter-annual dynamics among lakes within a district, was quantified as the Pearson product-moment correlation (r) between two lakes with observations paired by year. To determine if solute concentrations were directly related to interannual variations in precipitation quantity, we used regression analysis to fit district-wide slopes describing the relationship between each chemical variable and annual (June to May) and October to May (Oct–May) precipitation. 3. Among lakes in each of the three Ontario districts, the pattern of chemical response to interannual shifts in precipitation was spatially uniform. In these surface water- dominated districts, solute concentrations were generally a simple function of precipitation. Conservative solutes, like calcium and chloride, tended to be more synchronous and were negatively related to precipitation. Solutes such as silica, total phosphorus, and chlorophyll a, which are influenced by in-lake processes, were less synchronous and relationships with precipitation tended to be positive or absent. 4. In the groundwater-dominated Northern Highland lakes of Wisconsin, we observed spatial structure in drought response, with lowland lakes more synchronous than highland lakes. However, there was no evidence for a direct relationship between any solute and precipitation. Instead, increases in the concentration of the conservative ion calcium during drought were not followed by a symmetrical return to pre-drought conditions when precipitation returned to normal or above-average values. 5. For calcium, time lags in recovery from drought appeared related to hydrologic features in a complex way. In the highland Crystal Lake, calcium concentrations tracked lake stage inversely, with a return to pre-drought concentrations and lake stage five years after the drought. This pattern suggests strong evaporative controls. In contrast, after five years of normal precipitation, calcium in the lowland Sparkling Lake had not returned to pre-drought conditions despite a rebound in lake stage. This result suggests that calcium concentrations in lowland lakes were controlled more by regional groundwater flowpaths, which track climatic signals more slowly. 6. Temporal dynamics driven by climate were most similar among lakes in districts that have a relatively simple hydrology, such as ELA. Where hydrologic setting was more complex, as in the groundwater-dominated Northern Highland of Wisconsin, the expression of climate signals in lakes showed lags and spatial patterns related to landscape position. In general, we expect that landscape and lake-specific factors become increasingly important in lake districts with more heterogeneous hydrogeology, topography or land use. These strong chemical responses to climate need to be considered when interpreting the responses of lakes to other regional disturbances. [ABSTRACT FROM AUTHOR]